Cost Efficient GPU Cluster Management for Training and Inference of Deep Learning

Cost Efficient GPU Cluster Management for Training and Inference of Deep Learning

Expanding the scale of GPU-based deep learning (DL) clusters would bring not only accelerated AI services but also significant energy consumption costs. In this paper, we propose a cost efficient deep learning job allocation (CE-DLA) approach minimizing the energy consumption cost for the DL cluster...

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Bibliographic Details
Main Authors: Dong-Ki Kang, Ki-Beom Lee, Young-Chon Kim
Format: Article
Language:English
Published: MDPI AG 2022-01-01
Series:Energies
Subjects:
GPU-based cluster
deep learning
training
inference
job allocation
energy consumption cost
Online Access:https://www.mdpi.com/1996-1073/15/2/474

Internet

https://www.mdpi.com/1996-1073/15/2/474

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